Generating Search Results based on Proximate Computing Devices

ABSTRACT

Techniques include receiving a search query and an indication of a proximate device located near a user device from the user device and identifying one or more records included in a search data store based on the query and, e.g., the indication. In this example, the user device receives the indication from the proximate device via a local wireless network using which the proximate device communicates. Also in this example, each record includes record content (e.g., web links, documents, media files, software applications, or other data) and record information describing the content. In some examples, the techniques further include generating result scores for the identified records based on the indication and selecting one or more of the records based on the scores. The techniques also include selecting the record content from the identified (and, e.g., selected) records and transmitting the content to the user device as search results.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application No. 62/170,044 filed Jun. 2, 2015, which is hereby incorporated by reference in its entirety.

TECHNICAL FIELD

This disclosure generally relates to the field of search, and more particularly to techniques for generating and displaying search results on user devices.

BACKGROUND

In recent years, the use of computers, tablets, smartphones, smart watches, and other stationary and mobile computing devices has grown significantly. Additionally, the presence of network connectivity among these and other devices has also increased. Today, many consumer and industrial computing devices and appliances are capable of being connected to local computer networks and even the Internet. Users often perform searches (e.g., Internet searches) for web-pages, documents, media files, and other content using a variety of different computing devices, including such networked and Internet-enabled devices.

SUMMARY

In one example, a method includes receiving a search query and an indication of a proximate device from a user device. In this example, the proximate device is located proximate to the user device and configured to communicate via a local wireless network. Also in this example, the user device receives the indication of the proximate device from the proximate device via the local wireless network. The method further includes identifying one or more records based on the search query and the indication. In this example, each record includes record content and record information that describes the content. The method also includes selecting the record content from the identified records and transmitting the selected content to the user device as search results.

In another example, a method includes receiving a search query from a user device and identifying one or more records based on the query. In this example, each record includes record content and record information that describes the content. The method further includes receiving an indication of a proximate device from the user device. In this example, the proximate device is located proximate to the user device and configured to communicate via a local wireless network. Also in this example, the user device receives the indication of the proximate device from the proximate device via the local wireless network. The method still further includes generating a result score for each of the identified records based on the indication and selecting one or more of the identified records based on the one or more result scores. The method also includes selecting the record content from the selected records and transmitting the selected content to the user device as search results.

In another example, a system includes one or more computing devices configured to receive a search query and an indication of a proximate device from a user device. In this example, the proximate device is located proximate to the user device and configured to communicate via a local wireless network. Also in this example, the user device receives the indication of the proximate device from the proximate device via the local wireless network. The computing devices are further configured to identify one or more records based on the search query and the indication. In this example, each record includes record content and record information that describes the content. The computing devices are also configured to select the record content from the identified records and transmit the selected content to the user device as search results.

In another example, a system includes one or more computing devices configured to receive a search query from a user device and identify one or more records based on the query. In this example, each record includes record content and record information that describes the content. The computing devices are further configured to receive an indication of a proximate device from the user device. In this example, the proximate device is located proximate to the user device and configured to communicate via a local wireless network. Also in this example, the user device receives the indication of the proximate device from the proximate device via the local wireless network. The computing devices are still further configured to generate a result score for each of the identified records based on the indication and select one or more of the identified records based on the one or more result scores. The computing devices are also configured to select the record content from the selected records and transmit the selected content to the user device as search results.

BRIEF DESCRIPTION OF DRAWINGS

The details of one or more examples are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims.

FIG. 1 depicts an example environment that includes a search system and one or more user devices, proximate devices, and data sources that communicate via a network.

FIG. 2 depicts an example user device in communication with one or more example proximate devices and an example search system.

FIG. 3A is a functional block diagram of an example search system.

FIG. 3B is a functional block diagram of an example search module.

FIGS. 4A-4B depict example records included in an example search data store.

FIGS. 5A-5B are flow diagrams that illustrate example methods for generating search results based on proximate devices using a search system.

FIG. 6 is a flow diagram that illustrates an example method for generating search results based on proximate devices using a user device.

FIGS. 7A-7B depict example graphical user interfaces (GUIs) that may be generated on a user device according to the present disclosure.

DETAILED DESCRIPTION

The figures and the following description relate to example implementations by way of illustration only. It should be noted that from the following discussion, alternative implementations of the structures and methods disclosed herein will be readily recognized as viable alternatives that may be employed without departing from the scope of this disclosure.

The present disclosure generally relates to the field of search, and, more particularly, to techniques for generating and displaying search results on user devices. Using the techniques disclosed herein, in some examples, improve search query understanding and search result relevance. According to the disclosed techniques, a user device (e.g., a smart watch, smartphone, tablet computer, or laptop computer) may be located proximate to (e.g., nearby) one or more other devices (e.g., one or more consumer and/or industrial devices) that are capable of indicating their proximity to the user device. In other words, the proximate devices may be capable of indicating their presence near the user device to the device. For example, the proximate devices may include one or more network-connected (e.g., communicatively coupled via a computer network, or “networked”) computing devices and/or appliances. In some examples, the proximate devices may include any of networked desktop computers, printers, routers, smart televisions, gaming consoles, and wireless speakers. Additionally, or alternatively, the proximate devices may include any of networked home thermostats, light switches, refrigerators, microwaves, toasters, crock-pots, and other home and kitchen devices and appliances. In some examples, the proximate devices may be networked using any of Wi-Fi, Bluetooth, near-field communication (NFC), ZigBee, Z-Wave, radio frequency identification (RFID), and/or other short-range local wireless communication protocols, interfaces, and technologies. In these examples, the proximate devices may be further networked using any of Ethernet, USB, optical fiber, power line and/or other wired communication protocols, interfaces, and technologies. As a specific example, the proximate devices may include one or more devices commonly referred to as “Internet of Things” (IoT) devices that are connected to a local network and, e.g., the Internet, via a wired and/or wireless communications interface. In this disclosure, the user device may include any computing device that is capable of connecting to and interacting with one or more of the proximate devices via any of the local wireless communication protocols, interfaces, and technologies described herein. In some examples, the user device may also be capable of connecting to and interacting with other computing devices via any of the wired communication protocols, interfaces, and technologies described herein.

According to the disclosed techniques, the proximate devices may be configured to indicate their proximity to the user device via a local wireless communication protocol, interface, or technology (e.g., any of the local wireless communication protocols, interfaces, and technologies described herein). Specifically, each proximate device may be configured to transmit an indication of the device to the user device via a short-range local wireless network (e.g., Wi-Fi, Bluetooth, or NFC). A local wireless network, as used herein, may refer to any communication protocol, interface, or technology that enables two or more computing devices to exchange data wirelessly over a relatively short distance (e.g., up to 10-100 meters). Using the local wireless network, a first computing device may transmit data wirelessly to a second, different computing device. In some examples, the second computing device may also transmit data wirelessly to the first computing device using the local wireless network. As a result, the proximate device transmitting the indication of the device to the user device via the short-range local wireless network may indicate that the proximate device is located proximate to (e.g., nearby) the user device. In some examples, the proximate device may transmit the indication to the user device as part of actively communicating with the user device (e.g., the proximate device may be communicatively coupled with the user device). In other examples, the proximate device may transmit the indication to the user device as part of (e.g., in response to) the user device scanning for, or “pinging” (e.g., querying to determine a connection with, or activity of) nearby devices using a local wireless network (e.g., Wi-Fi, or Bluetooth). In still other examples, the proximate device may transmit the indication as part of a transmission (e.g., a broadcast) intended for one or more computing devices other than the user device (e.g., as part of pairing the proximate device with, or transmitting data to, the computing devices). In these examples, the user device may receive the indication as a result of the transmission (e.g., by listening for and/or receiving the transmission). In other words, in some examples, the user device may not transmit any data to the identified proximate device as part of receiving the indication of the proximate device from the proximate device. In this manner, the user device may receive the indication as a result of various types of data transmission by the proximate device, including data transmission directly to the user device, and data transmission to one or more other computing devices. As described herein, the proximate device may transmit the indication to the user device over a local wireless network. In some examples, the proximate device may transmit the indication wirelessly using an intermediate device, such as a wireless router, a Wi-Fi adapter, or a Bluetooth adapter.

In this disclosure, one or more such indications received by the user device from one or more proximate devices that are located proximate to the user device may be referred to as a “snapshot” of the proximate devices from the standpoint of the user device. According to the disclosed techniques, upon receiving the indications (e.g., the snapshot), the user device may identify the proximate devices as located proximate to the user device. As one example, the user device may identify each proximate device as being located proximate to the user device. As another example, the user device may identify a subset of the proximate devices as being located proximate to the user device. As a specific example, the user device may identify one or more of the proximate devices as being located the most proximate (e.g., closest) to the user device.

Upon identifying the one or more proximate devices, the user device (e.g., using a search system) may generate one or more search results based on the devices and a search query specified by a user of the device. As described herein, the search results may include or reference a variety of different types of information and content. In particular, the user device (e.g., the search system) may generate the search results such that the results are relevant to both the search query and to one or more aspects of the identified proximate devices, their types (e.g., device categories), and/or their specific states at the time the devices were identified. Upon generating the search results, the user device may display the results to the user.

In this manner, the techniques described herein may improve search query understanding and search result relevance. As one example, the identified proximate devices, their types, and/or their states may serve as useful contextual data related to the user and the user's behavior (e.g., the user's intent, or need) with respect to the search query. By performing searches for a variety of different types of information and content using the search query and the identified proximate devices, their types, and/or their states as search parameters, the techniques may improve understanding of the query. Additionally, by uncovering information (e.g., content) that is both responsive to (e.g., matches) the search query and relevant to the identified proximate devices, their types, and/or their states, the techniques may further enable generating search results that are more relevant to the user than those generated using the query alone.

FIG. 1 is a functional block diagram that illustrates an example environment including a search system 100 and one or more user devices 102, proximate devices 104, and data sources 108 that communicate via a network 106. The network 106 through which the above-described systems and devices communicate may include any type of network, such as a local area network (LAN), a wide area network (WAN), and/or the Internet. As shown in FIG. 1, the search system 100 includes a search module 110, a search data store 112, and a result generation module 114, which are described in greater detail herein.

In the example of FIG. 1, the search system 100 receives a search query and one or more indications of one or more of the proximate device(s) 104, their types, and/or their states from one of the user device(s) 102. The search system 100 then generates one or more search results in response to receiving the search query and the indications. Specifically, the search system 100 generates the search results based on the search query and the indications, as well as using information included in one or more records stored in the search data store 112. In this example, each record may include or reference a variety of different content (e.g., record content), such as web pages (e.g., web links), documents (e.g., text), media (e.g., image, audio, and/or video) files, software applications (apps), and/or states of software apps. The search system 100 selects the record content from the records and transmits the content to the user device 102 as the search results. Each record may also include other information (e.g., record information, such as text, and/or record identifiers (IDs)) which the search system 100 may use to identify the records in the search data store 112. The search system 100 transmits the search results, including the record content, to the user device 102, which displays the results to a user of the device 102 as one or more user selectable links that include the content.

Specifically, to generate the search results, the search module 110 may identify one or more records included in the search data store 112 based on the search query and, e.g., the indications of the one or more of the proximate device(s) 104, their types, and/or their states. Initially, the search module 110 may analyze the search query. The search module 110 may then identify one or more records included in the search data store 112 based on the (e.g., analyzed) search query and, e.g., the indications. For example, the search module 110 may identify the records based on (e.g., text) matches between terms of the search query and terms of information included in the records. In some examples, the search module 110 may further identify the records based on (e.g., text) matches between the indications and information included in the records. The search module 110 may then process (e.g., score) the identified records. For example, the search module 110 may determine how well the identified records match the search query and, e.g., various aspects of one or more of the proximate device(s) 104, as specified by the indications. The search module 110 may then select one or more of the identified records that best match the search query and, e.g., various aspects of the proximate devices 104, and transmit indications (e.g., IDs) of the selected records to the result generation module 114.

The result generation module 114 may identify the records selected by the search module 110 in the search data store 112 using the received indications (e.g., IDs). The result generation module 114 may then select record content (e.g., web links, documents, media files, access mechanisms (AMs), such as app AMs (AAMs), web AMs (WAMs), and/or app download addresses (ADAs)) from the identified records. The result generation module 114 may transmit the selected record content to the user device 102 as the search results. In some examples, the result generation module 114 may transmit additional data with the record content to the user device 102. For example, the search module 110 may generate result scores for the records from which the record content is selected (e.g., using values of metrics associated with the persons, places, or things described in the records, various features of the search query, and, e.g., various features of the proximate device(s) 104 as specified by the indications). As such, each record (e.g., the corresponding record content) may be associated with a result score that indicates a rank of the record (e.g., the content) relative to the other records (e.g., the corresponding record content of each record). In some examples, the result generation module 114 may transmit the result score associated with each record to the user device 102 with the record content of each record. Additionally, or alternatively, the result generation module 114 may transmit link data associated with each record (e.g., with the corresponding record content) to the user device 102.

Using the techniques described herein may, in some examples, enable generating search results that are relatively more relevant to the search query compared to search results generated using other techniques (e.g., based on the query alone). As a specific example, in response to receiving a search query “toast” from the user and upon identifying a proximate smart toaster 104 (e.g., a Bugatti Noun Toaster), the user device 102 may transmit the query and an indication of the toaster 104 (e.g., its model name/number, or general type) to the search system 100 (e.g., as part of a query wrapper). In this example, the user device 102 may receive from the search system 100 search results that are both responsive to the search query and relevant to the smart toaster 104. Specifically, the search results may specify one or more web pages, documents, media files, apps, and/or states of apps that are related to bread toast or bread toasters, rather than, e.g., to raising a glass and making a speech (e.g., an alternative interpretation of the term “toast”). The user device 102 may display an indication of the web pages, documents, files, apps, and/or states to the user as one or more user selectable links that, when selected by the user, cause the device 102 to access the web pages, documents, or media files, download and install the apps, and/or launch apps and set the apps into the states.

Using the techniques may also enable generating search results that are directly applicable to those of the proximate device(s) 104 that are located proximate to the user device(s) 102. Specifically, the techniques may include using indications of the proximate device(s) 104, their types, and/or their states (e.g., specific model names/numbers or device IDs, type IDs, and/or state IDs) to generate search results that are both responsive to user-specified search queries and directly applicable to the device(s) 104. As one example, upon transmitting the search query and the indications of the proximate device(s) 104, their types, and/or their states to the search system 100, as described herein, the user device 102 may be configured to receive search results that specify one or more web resources or files associated with the device(s) 104, types, and/or states from the system 100. For example, the search results may include any of web pages (e.g., web links), documents (e.g., text), images, audio files, and/or video files that describe or relate to the proximate device(s) 104, types, and/or states. As a specific example, in response to receiving a search query “crock-pot” from a user and upon identifying a proximate smart crock-pot 104 (e.g., a Crock-Pot® Smart Slow Cooker with WeMo®), the user device 102 may transmit the query and an indication of the crock-pot 104 to the search system 100 (e.g., as part of a query wrapper). In this example, the user device 102 may receive from the search system 100 search results that are both responsive to the search query and directly applicable to the smart crock-pot 104. For example, the search results may specify one or more web pages, documents, and/or (e.g., media) files associated with the smart crock-pot 104 (e.g., user manuals, walkthrough video tutorials, etc.). The user device 102 may display an indication of the web pages, documents, and/or files to the user as one or more user selectable links that, when selected by the user, cause the device 102 to access these resources.

As another example, upon transmitting the search query and the indications to the search system 100, the user device 102 may be configured to receive search results that specify one or more native apps (e.g., app search results) associated with the proximate device(s) 104, types, and/or states from the search system 100. For example, the search results may include any of text and image data that describe the apps and ADAs that enable the user device 102 to download and install the apps. In a specific example, in response to receiving a search query “print” from a user and upon identifying a proximate networked printer 104 (e.g., the HP® Envy 4502 printer), the user device 102 may transmit the query and an indication of the printer 104 to the search system 100 (e.g., in a query wrapper). In this example, the user device 102 may receive from the search system 100 search results that are both responsive to the search query and specify one or more native apps that are directly applicable to the networked printer 104. For example, the search results may include one or more ADAs that each direct the user device 102 (e.g., in response to a user input) to a location (e.g., a digital distribution platform) from which the device 102 may download a native app associated with the networked printer 104 (e.g., the HP® All-in-One Printer Remote) that enables the user to print documents and/or images using the printer 104. The user device 102 may display the ADAs (and, e.g., text and/or images included in the search results) to the user as one or more user selectable links that, when selected by the user, cause the device 102 to download and install the native app. Additionally, or alternatively, the user device 102 may receive other types of search results (e.g., a device driver for the networked printer 104) that are both responsive to the search query and directly applicable to the printer 104.

As still another example, upon transmitting the search query and the indications to the search system 100, the user device 102 may be configured to receive search results that specify one or more states of native apps (e.g., app state search results) associated with the proximate device(s) 104, types, and/or states from the search system 100. For example, the search results may include any of text and image (e.g., link) data and one or more AAMs, WAMs, and ADAs that describe the states and enable the user device 102 to access the states (e.g., by first downloading and installing the corresponding app). In a specific example, in response to receiving a search query “unlock” from a user and upon identifying a proximate smart door lock 104 (e.g., an August® Smart Lock), the user device 102 may transmit the query and an indication of the lock 104 to the search system 100 (e.g., in a query wrapper). In this example, the user device 102 may receive from the search system 100 search results that are both responsive to the search query and specify one or more states of a native app that are directly applicable to the smart door lock 104. For example, the search results may include one or more AAMs that each direct the user device 102 to launch a native app associated with the smart door lock 104 (e.g., the August® Smart Lock App) and set the app into a state that unlocks the lock 104. The user device 102 may display the AAMs to the user as one or more user selectable links that, when selected by the user, cause the device 102 to launch the native app and set the app into the corresponding states. Upon being launched and set into any of the states, the native app may further (e.g., automatically, or via additional user input) cause the smart door lock 104 to unlock. In some examples, the search results may also include one or more WAMs that, when selected by the user (e.g., as part of a user selectable link), direct the user device 102 to a web equivalent (e.g., a web page) of one or more of the states (e.g., in cases where the user device 102 does not have the native app installed). In other examples, the search results may also include one or more ADAs that direct the user device 102 (e.g., in response to a user input) to a location (e.g., a digital distribution platform) from which the device 102 may download the native app, e.g., prior to launching and setting it into any of the states previously described.

In some examples, the search results may specify web resources, files, apps, and/or states of apps that are directly applicable, complementary, or tangentially related to states of the proximate device(s) 104. As one example, the search results may specify states of apps for hot or cold food items or beverages depending on whether a (e.g., specific model, or a general type of) networked home thermostat located proximate to the user device 102 indicates a particular indoor or outdoor temperature, temperature range, or ongoing mode of operation (e.g., cooling, or heating). In these examples, the states of the proximate devices 104, or of proximate device types, may be indicated using state IDs that include textual and/or numerical data that describes the states of the devices 104 (e.g., “75° F.,” “day's range: 45° F.-55° F.,” “cooling” or “heating”). The search system 100 may identify state records 400 and/or rank the records 400 based on matches between the state IDs and information included in the records 400, as described herein.

In other examples, the search results may specify web resources, files, apps, and/or states of apps that are directly applicable, complementary, or tangentially related to other properties (e.g., so-called “external” factors) of the user device 102 and/or the user that are derived based on the states of the proximate device(s) 104. For example, the user device 102 and/or the search system 100 may be configured to learn a particular user behavior associated with the user (and, e.g., other users) as a function of one or more states of the proximate device(s) 104. As one example, the user device 102 and/or the search system 100 may determine that, given a particular state of a specific proximate device 104 (e.g., a networked home thermostat in the process of heating or cooling), the user performing searches for states of apps corresponding to restaurants may select search results specifying some restaurants over others. The user device 102 and/or the search system 100 may generate a mapping between the state (e.g., a corresponding state ID including text and/or numbers) and the information (e.g., text) included in the state records 400 associated with the selected search results. The user device 102 and/or the search system 100 may then use this mapping as part of generating search results for subsequent searches. For example, the search system 100 may, given the same state of the proximate device 104 at a later point in time, identify and/or rank state records 400 based on matches between the information associated with the state by the mapping and information included in the records 400, in a similar manner as described herein.

In this disclosure, an app may refer to computer software that causes a computing device (e.g., one of the user device(s) 102) to perform a task. In some examples, an app may be referred to as a “program.” Example apps include word processing apps, spreadsheet apps, messaging apps, media streaming apps, social networking apps, and games. Apps can be executed on a variety of different computing devices, including mobile computing devices, such as smartphones, tablets, and wearable computing devices (e.g., smart headsets and/or smart watches). Apps can also be executed on other types of computing devices having other form factors, such as laptop computers, desktop computers, or other consumer electronic devices. In some examples, apps may be installed on a computing device prior to a user purchasing the device. In other examples, the user may download and install apps on the computing device after purchasing the device. A native app, as used herein, may refer to an app that is installed and executed on a user device 102. A web-based app, in turn, may refer to an app that is accessible from a user device 102 via a web browser app included on the device 102.

An AM, as used herein, may include any of an AAM, a WAM, and an ADA. As such, a user device 102 of the present disclosure may use an AM to access the functionality provided by a native or a web-based app. For example, a user of the user device 102 may select a user selectable link that includes the AM to access the functionality of the app. An AAM may be a string that references a native app and indicates one or more operations for a user device 102 (e.g., the app) to perform. If a user of the user device 102 selects a user selectable link that includes the AAM, the device 102 may launch the native app and (e.g., cause the app to) perform the operations. In other words, the user selecting the user selectable link may cause the user device 102 to launch the native app and set the app into an app state (e.g., in which the app displays a GUI, or screen) that corresponds to the operations. As a result, the native app may be configured to display one or more products, services, or vendors, to the user, e.g., via a display device of the user device 102. In this manner, the AAM may specify the app state of the native app. The app state, in turn, may refer to the operations indicated by the AAM and/or the outcome of the native app performing the operations in response to the user selecting the user selectable link that includes the AAM.

A WAM may include a resource identifier that references a web resource (e.g., a page of a web-based app, or website). For example, the WAM may include a uniform resource locator (URL) (i.e., a web address) used with the hypertext transfer protocol (HTTP). If a user of a user device 102 selects a user selectable link that includes the WAM, the device 102 may launch a web browser app included on the device 102 and retrieve the web resource referenced by the resource identifier. Stated another way, if the user selects the user selectable link, the user device 102 may launch the web browser app and access an app state (e.g., a page) of a web-based app, or website, specified by the WAM. In some examples, a WAM included in an app state record with an AAM may specify an app state of a web-based app that is an equivalent of (e.g., analogous to) an app state of a native app specified by the AAM.

An ADA may specify a location (e.g., a digital distribution platform, such as Google Play® by Google Inc.) where a native app (e.g., a native app referenced by an AAM) may be downloaded. In some examples, an app state record may include an ADA with an AAM (and, e.g., a WAM). In these examples, the ADA may specify a location from which a native app referenced by the AAM may be downloaded.

In some examples, the search system 100 may transmit the search results, including the record content, to the user device 102 with additional data. For example, the search system 100 may transmit link (e.g., text and/or image) data that the user device 102 may use to generate the user selectable links for the record content. Each user selectable link may include a portion of the link (e.g., text and/or image) data that the user of the user device 102 may select (e.g., touch, or “click on”). Each user selectable link may also be associated with a corresponding portion of the record content included in the search results, such that when the user selects the link, the user device 102 access the content. For example, the user device 102 may access a web page using a web browser app, download and/or open a document or a media file, or launch a native or web-based app referenced by a corresponding AM and cause the app to perform one or more operations indicated by the AM. The text and/or image data of the user selectable link may indicate the web page, document, media file, or operations or function that the user device 102 accesses performs in response to selection of the link. For example, if the user selectable link is for a song in a native or web-based music player app, the text and/or image data may indicate that the user device 102 will launch the app and that the app will play the song when the user selects the link. In some examples, when the user selects the user selectable link, the user device 102 downloads a native app referenced by a corresponding AM and installs the app. Example user selectable links are described with reference to FIGS. 7A-7B.

As described herein, the search system 100 uses data (e.g., records) included in the search data store 112 to generate search results based on search queries and indications of the proximate device(s) 104, their types, and/or their states received from the user device(s) 102. The search data store 112 may include one or more databases, indices (e.g., inverted indices), tables, files, or other data structures that may be used to implement the techniques of this disclosure. In some examples, the search data store 112 may be included in one or more storage devices. The search data store 112 includes one or more records. Each record may include a wide variety of different types of data, as described herein. For example, each record may include, among other information, a record ID, record information, and record content. A record ID of a record may uniquely identify the record among other records included in the search data store 112. Record information of a record may describe the record content included in, or referenced by the record. Example records are described with reference to FIGS. 4A-4B.

As described herein, the search system 100 receives the search query and the indications of the proximate device(s) 104, their types, and/or their states from the user device 102 and generates the search results based on the query and the indications. The search query may include text, numbers, and/or symbols (e.g., punctuation) entered into the user device 102 by the user. For example, the user may have entered the search query into a search field, or “search box,” of a search app (e.g., a search app 204, as shown in FIG. 2) included on the user device 102. The user may have entered the search query using a touchscreen keypad, a mechanical keypad, and/or via speech recognition techniques and transmitted the query to the search system 100 using the search app. In some examples, the search app may be a native app (e.g., any of one or more native apps 206, as further shown in FIG. 2) dedicated to search, or a more general app, such as a web browser app (e.g., a web browser app 202, as also shown in FIG. 2). The indications of the proximate device(s) 104, their types, and/or their states may include text, numbers, symbols (e.g., punctuation), and/or any machine-readable (e.g., binary) data used by the user device 102 (e.g., the search app) to represent the device(s) 104, types, and/or states. For example, the indications may include or reference any of device IDs, type IDs, and state IDs. In some examples, the search app may identify the proximate device(s) 104, determine their types and/or their states, and transmit the indications to the search system 100 (e.g., with the search query). In further examples, the user device 102 may transmit additional data to the search system 100 with the search query and the indications of the proximate device(s) 104, their types, and/or their states. The search query, the indications, and the additional data may be referred to herein as a query wrapper. The additional data may include geo-location data associated with the user device 102, platform data for the device 102 (e.g., a type and/or a version of the device 102, an operating system (OS), and/or a web browser app of the device 102), an identity of the user (e.g., a username), partner specific data, and other data. The user device 102 may transmit the query wrapper to the search system 100, which may use the search query, the indications, and/or the additional data included in the wrapper to generate the search results and provide the results to the device 102.

The user device(s) 102 may be any computing devices capable of providing search queries and indications of the proximate device(s) 104, their types, and/or their states to the search system 100 and receiving search results from the system 100. The user device(s) 102 may include any of smartphones, and tablet, laptop, or desktop computers. The user device(s) 102 may also include any computing devices having other form factors, e.g., computing devices included in vehicles, gaming devices, televisions, or other appliances (e.g., networked home automation devices and home appliances). The user device(s) 102 may use a variety of different operating systems or platforms (e.g., OS 200, as shown in FIG. 2). In instances where a user device 102 is a mobile device, the device 102 may operate using an OS such as ANDROID® by Google Inc., IOS® by Apple Inc., or WINDOWS PHONE® by Microsoft Corporation. In instances where the user device 102 is a laptop or desktop computing device, the device 102 may use an OS such as MICROSOFT WINDOWS® by Microsoft Corporation, MAC OS® by Apple Inc., or LINUX® (LINUX is the registered trademark of Linus Torvalds in the U.S. and other countries). The user device(s) 102 may also interact with the search system 100 using operating systems other than those described herein, whether presently available or developed in the future.

The user device(s) 102 may communicate with the search system 100 via the network 106. In general, the user device(s) 102 may communicate with the search system 100 using any app that can transmit search queries and indications of the proximate device(s) 104, their types, and/or their states, to the system 100 and receive search results from the system 100. In some examples, the user device(s) 102 may include an app that is dedicated to interfacing with the search system 100, such as an app dedicated to search. In other examples, the user device(s) 102 may communicate with the search system 100 using a more general app, such as a web browser app. An app included on a user device 102 to communicate with the search system 100 may include a GUI with a search field, or “box,” into which users may enter search queries, e.g., using a touchscreen, physical keyboard, a speech-to-text program, or other form of user input available on the device 102. In some examples, the app may also be configured to identify (e.g., via a proximate device identification module) one or more of the proximate device(s) 104 that are located proximate to the user device 102 and transmit one or more indications of the identified devices 104, their types, and/or their states to the search system 100.

The user device 102 may use a GUI of a search app, or a more general app, included on the device 102 to display search results to the user. The user device 102 may also use the GUI to receive search queries from the user and transmit the queries and indications of the proximate device(s) 104, their types, and/or their states to the search system 100. The GUI may display the search results to the user in a variety of different ways, depending on the information transmitted to the user device 102 from the search system 100. In some examples, the search system 100 may transmit the search results (e.g., record content) to the user device 102 with result scores, link data, and/or other information used to generate and display (e.g., rank) one or more user selectable links for the results. In some examples, the GUI may display the search results to the user as a list of the user selectable links, including text and/or image data. For example, the text and/or images data may indicate the record content specified by (e.g., included in) the search results. In some examples, the GUI may display the search results as the list of the user selectable links arranged under a search field into which the user has entered a search query. The GUI may arrange the user selectable links by result scores associated with the links, i.e., with the record content for which the links are generated, or using other logic. In some examples, the GUI may also group the user selectable links by various headers.

The data source(s) 104 may be sources of data that the search system 100 may use to generate and/or update the search data store 112. For example, the search system 100 may use the data source(s) 104 to generate and/or update one or more databases, indices, tables, files, or other data structures included in the search data store 112. The search system 100 may generate new records and update existing records based on data retrieved from the data source(s) 104. For example, the search system 100 may include modules that generate new records and/or update existing records based on the data retrieved from the data source(s) 104. In some examples, some or all of the data included in the search data store 112 (e.g., one or more records) may be manually generated by a human operator.

The data source(s) 104 may include a variety of different data providers. For example, the data source(s) 104 may include data from app developers, such as app developer websites and data feeds provided by app developers. The data source(s) 104 may also include operators of digital distribution platforms configured to distribute apps to user devices 102. The data source(s) 104 may further include other websites, such as websites that include web logs (i.e., blogs), app reviews, or other data related to apps. Additionally, the data source(s) 104 may include social networking sites, such as “FACEBOOK®” by Facebook Inc. (e.g., Facebook posts) and “TWITTER®” by Twitter Inc. (e.g., text from tweets). The data source(s) 104 may also include online databases and websites that include data related to movies, television programs, music, and restaurants. The data source(s) 104 may further include other types of data sources, which may have various types of content and update rates.

In some examples, the search system 100 may retrieve data from the data source(s) 104, including any type of data related to web links, documents, media files, apps, and states of apps. The search system 100 may then generate one or more records based on the data and store the records in the search data store 112. In other examples, some or all of the data included in the records (e.g., record information) may be manually generated by a human operator. In some examples, the data included in the records may be updated over time so that the search system 100 may provide up-to-date search results in response to search queries and indications of the proximate device(s) 104, their types, and/or their states received from the user device(s) 102.

FIG. 2 illustrates an example of one of the user device(s) 102 in communication with one or more of the proximate device(s) 104 and the search system 100. Specifically, FIG. 2 depicts example interactions and data exchanged among the user device 102, proximate devices 104, and search system 100. As shown in FIG. 2, the user device 102 may initially receive a search query 116 from a user of the device 102. For example, the user may have entered the search query 116 into a search field 117 of a GUI 115 of a search app 204 included on the user device 102. As also shown, the user device 102 may further identify one or more of the proximate device(s) 104. In some examples, the user device 102 may identify the proximate device(s) 104 prior to, during (e.g., in response to), or following the user entering the search query 130 as described herein. For example, the user device 102 may identify the proximate devices 104 using a proximate device identification module 208 included on the device 102. For instance, the proximate device identification module 208 may be configured to identify one or more of the proximate device(s) 104 that are located proximate to (e.g., nearby) the user device 102. In some examples, the proximate device identification module 208 may include a device determination module 210 configured to determine a model name, a model number, and/or a device ID of each of one or more of the identified proximate devices 104. In other examples, the user device 102 may further determine one or more types of the identified proximate devices 104 (e.g., via one or more type IDs associated with the types). For example, the proximate device identification module 208 may include a device type determination module 212 configured to determine the types of the identified proximate devices 104. Additionally, or alternatively, the user device 102 may determine one or more states of the identified proximate devices 104 (e.g., via one or more state IDs). For example, the proximate device identification module 208 may include a device state determination module 214 configured to determine the states.

As shown in FIG. 2, the user device 102 may transmit a query wrapper to the search system 100. The query wrapper may include the search query 116 and one or more indications of the identified proximate devices 104, their types, and/or their states 118 (e.g., the one or more device IDs, type IDs, and/or state IDs). The query wrapper may also include geo-location data, platform data, and/or other information (e.g., an IP address) associated with the user, the user device 102, the query 116, and/or the identified proximate devices 104. For example, the user may have caused the user device 102 (e.g., the search app 204) to submit the query wrapper including the search query 116 and the indications 118 to the search system 100 by selecting a search button 119 also included in the GUI 115 of the search app 204.

Upon receiving the query wrapper from the user device 102, the search system 100 may generate one or more search results 120 based on the search query 116 and the indications 118 included in the wrapper. As described herein, to generate the search results 120, the search system 100 may identify one or more records included in the search data store 112 using the search query 116 and, e.g., the indications 118. As also described herein, the search system 100 may further generate results scores for the identified records, e.g., based on the indications 118. The search system 100 may then transmit the search results 120 to the user device 102. As shown in FIG. 2, the search results 120 may include or reference one or more web pages (e.g., web links), documents (e.g., text), media (e.g., image, audio, and/or video) files, AMs (e.g., AAMs, WAMs, and/or ADAs specifying native or web-based apps and/or states of the apps), result scores, link data, and/or other information included in the identified records.

In the example of FIG. 2, upon receiving the search results 120 from the search system 100, the user device 102 may display the results 120 as one or more user selectable links. For example, the user device 102 may generate the user selectable links such that each link is associated with (e.g., includes) a portion of the information included in the search results 120. The user device 102 may generate the user selectable links using the link data also included in the search results 120. For example, the link data may include any of text and image data describing the information included in the search results 120. In this manner, the link data included in (e.g., used to generate) each user selectable link may describe the portion of the information included in the search results 120 associated with the link. The user device 102 may further arrange (e.g., order, or rank) the user selectable links to display the links to the user based on the result scores also included in the search results 120. For example, the user device 102 may assign each user selectable link the result score associated with the record from which the information included in the link was selected. The user device 102 may then order the user selectable links based on the result scores (e.g., display higher-ranking links higher in a list of user selectable links). Example search results 120 displayed to a user of a user device 102 as user selectable links are described with reference to FIGS. 7A-7B.

FIG. 3A illustrates an example search system 100. The search system 100 of FIG. 3A includes the search module 100, search data store 112, and result generation module 114. The search module 110 identifies records 400 included in the search data store 112 based on search queries 116 and based on indications of proximate devices 104, their types, and/or their states 118 received from the user device(s) 102. Initially, the search module 110 may optionally analyze a search query 116 received from a user device 102. The search module 110 may then identify one or more records 400 included in the search data store 112 based on the (e.g., analyzed) search query 116 and based on an indication of a proximate device 104, its type, and/or its state (e.g., represented using a device ID, a type ID, and/or a state ID) also received from the user device 102. For example, the search module 110 may identify the records 400 based on (e.g., text) matches between terms of the search query 116 and terms of information (e.g., record information and/or record IDs) included in the identified records 400. In some examples, the search module 110 may further identify the records 400 based on matches between (e.g., terms of) the indication 118 (e.g., the device ID, type ID, and/or state ID) and the information included in the identified records 400. The search module 110 may then process (e.g., generate result scores for) the identified records 400. For example, the search module 110 may generate result scores for the records 400 based on how well the records 400 match the search query 116 and, e.g., the indication 118 (e.g., terms of the indication 118, such as the device ID, type ID, and/or state ID). The search module 110 may further select one or more of the identified records 400 that best match the search query 116 and the indication 118 (e.g., select one or more records 400 having the highest result scores). The search module 110 may transmit record IDs 122 associated with (e.g., included in) the selected records 400 to the result generation module 114. The result generation module 114 may identify the records 400 selected by the search module 110 in the search data store 112 using the received record IDs 122 and select record content (e.g., web links, documents, media files, AAMs, WAMs, ADAs, and/or other information) from the identified records 400. The result generation module 114 may then transmit the selected record content to the user device 102 as one or more search results 120.

FIG. 3B illustrates an example of the search module 110 described with reference to FIG. 3A. The search module 110 of FIG. 3B includes a query analysis module 300, a consideration set generation module (hereinafter, “set generation module”) 302, and a consideration set processing module (hereinafter, “set processing module”) 304. The query analysis module 300 may receive a search query 116 (e.g., as part of a query wrapper) from a user device 102 and analyze the query 116. For example, the query analysis module 300 may perform any of tokenization, filtering, stemming, synonymization, and stop word removal with respect to the query 116. The set generation module 302 may identify one or more records 400 included in the search data store 112 based on the search query 116 and based on one or more indications of one or more of the proximate device(s) 104, their types, and/or their states 118 (e.g., one or more device IDs, type IDs, and/or state IDs) also received from the user device 102.

In some examples, the set generation module 302 may identify a given record 400 based on whether a particular proximate device 104 (e.g., having a specific model name, model number, and/or device ID) is located proximate to the user device 102, as specified by the indications 118. In other examples, the set generation module 302 may identify the record 400 based on whether a particular proximate device type (e.g., having a specific type ID) is located proximate to the user device 102, as specified by the indications 118. Additionally, or alternatively, the set generation module 302 may identify the record 400 based on whether a specific proximate device, or a general device type, having a particular state (e.g., having a given state ID) is located proximate to the user device 102, as specified by the indications 118. The identified records 400 may be referred to herein as a “consideration set.” In some examples, the set generation module 302 may identify the records 400 of the consideration set based on one or more (e.g., text) matches between one or more terms of the search query 116 and one or more terms of information (e.g., record information and/or record IDs) included in the identified records 400. For example, the set generation module 302 may identify the records 400 based on matches between tokens generated by the query analysis module 300 and words included in the records 400 (e.g., in record information and/or record IDs of the records 400). In some examples, the set generation module 302 may further identify the records 400 of the consideration set based on one or more (e.g., text) matches between the indications of the proximate devices 104, their types, and/or their states 118 (e.g., between the device IDs, type IDs, and/or state IDs included in, or referenced by the indications 118) and the information included in the records 400 (e.g., the record information and/or record IDs). For example, the set generation module 302 may identify one or more records 400 included in the search data store 112 that specify any aspect of the indications of the proximate devices 104, their types, and/or their states 118 (e.g., that include any of the associated device IDs, type IDs, and/or state IDs). As a specific example, the set generation module 302 may identify the records 400 using the search query 116 and, e.g., the indications 118, as inputs to Lucene® information retrieval software developed by the Apache Software Foundation (hereinafter, “Lucene”). In this example, the record information included in the records 400 may be indexed using inverted indexing techniques, which may allow mapping one or more terms of the search query 116 and (e.g., one or more terms of) the indications 118 (e.g., device IDs, type IDs, and/or state IDs) to the record information included in the records 400.

The set processing module 304 processes (e.g., generates result scores for, or “scores”) the records 400 included in the consideration set and transmits one or more record IDs 122 associated with (e.g. included in) the processed records 400 to the result generation module 114. In some examples, the set processing module 304 scores the records 400 by generating a result score for each record 400. In these examples, the result scores may be transmitted to the result generation module 114 along with the record IDs 122 for the records 400 of the consideration set. The set processing module 304 may generate the result scores for the records 400 in a variety of different ways. In some examples, the set processing module 304 generates a result score for a record 400 based on one or more scoring features. The scoring features may be associated with the record 400, the search query 116, and/or one or more indications of the proximate device(s) 104, their types, and/or their states that resulted in identification of the record 400 by the set generation module 302. A scoring feature for the record 400 (e.g., a “record scoring feature”) may be based on any data associated with the record 400, e.g., data included in the record information of the record 400. Example record scoring features for the record 400 include popularity and/or ratings (e.g., user ratings) of a web page, document, media file, app, or state of an app specified by the record 400. Other example record scoring features include measurements associated with the record 400, such as how often the record 400 is retrieved during a search and how often user selectable links for record content included in the record 400 are selected by a user. Still other record scoring features include whether the record 400 specifies a web page, a document, a media file, an app, a state of an app, or any other data that is specific to the record 400. A scoring feature for the search query 116 (e.g., a “query scoring feature”) may include any data associated with the query 116. Example query scoring features for the search query 116 include a number of words in the query 116, popularity of the query 116, and an expected frequency of the words in search query 116. A scoring feature for the record 400 and the search query 116 (e.g., a “record-query scoring feature”) may include any data that may be generated based on information associated with both the record 400 and the query 116. Example record-query scoring features for the record 400 and the search query 116 include parameters that indicate how well terms of the query 116 match terms of the record information and/or the record ID of the record 400.

As described herein, in some examples, the set processing module 304 may generate a result score for a record 400 based on one or more indications of one or more of the proximate device(s) 104, their types, and/or their states 118 received from one of the user device(s) 102. In these examples, a “proximate device” scoring feature may include any aspects of the indications 118. As one example, a proximate device scoring feature may include one or more model names, model numbers, and/or device IDs specified by the indications 118. In this example, the set processing module 304 may generate the result score for the record 400 based on whether a particular proximate device 104 (e.g., having a specific model name, model number, and/or device ID) is located proximate to the user device 102, as specified by the indications 118. As another example, a proximate device scoring feature may include one or more type IDs specified by the indications 118. In this example, the set processing module 304 may generate the result score for the record 400 based on whether a particular proximate device type (e.g., having a specific type ID) is located proximate to the user device 102, as specified by the indications 118. As still another example, a proximate device scoring feature may include one or more state IDs specified by the indications 118. In this example, the set processing module 304 may generate the result score for the record 400 based on whether a specific proximate device, or a general device type, having a particular state (e.g., having a given state ID) is located proximate to the user device 102, as specified by the indications 118. In another example, a scoring feature for the record 400 and the indications 118 (e.g., a “record-proximate device” scoring feature) may include any data generated based on information associated with both the record 400 and the indications 118. Example record-proximate device scoring features include parameters that indicate how well (e.g., terms of) the indications 118 (e.g., the device IDs, type IDs, and/or state IDs) match terms of the record information and/or the record ID included in the record 400. In general, the set processing module 304 may generate the result score for the record 400 based on any combination of one or more record scoring features, query scoring features, record-query scoring features, proximate device scoring features, and record-proximate device scoring features.

The set processing module 304 may generate the result scores for the records 400 included in the consideration set based on one or more of the scoring features described herein and/or any additional scoring features. In some examples, the set processing module 304 may include one or more machine-learned models (e.g., a supervised learning model), such as a machine-learned relevance (MLR) model (e.g., including regression) configured to receive one or more scoring features. The machine-learned models may be further configured to generate the result scores for the records 400 based on one or more of the record scoring features, query scoring features, record-query scoring features, proximate device scoring features, and record-proximate device scoring features described herein. For example, the set processing module 304 may pair the search query 116 with each record 400 of the consideration set and compute a vector of features for each (query, record) pair. In some examples, the set processing module 304 may further pair the search query 116 and each record 400 with the indications of the proximate devices 104, their types, and/or their states 118, and compute a vector of features for each (query, proximate device/type/state, record) pair. In general, the vector of features may include one or more record scoring features, query scoring features, record-query scoring features, proximate device scoring features, and/or record-proximate device scoring features. The set processing module 304 may then input the vector of features into a machine-learned (e.g., MLR) model to calculate a result score for the corresponding record 400. In some examples, the machine-learned model may include a set of decision trees (e.g., gradient boosted decision trees), or a logistic probability formula. In further examples, the machine-learned task described herein may be framed as a semi-supervised learning task, where a minority of training data used to create the machine-learned model is labeled with human curated result scores, and the rest of the training data is used without human curated result score labels.

In some examples, the set processing module 304 may further select one or more of the records 400 included in the consideration set based on the result scores associated with the records 400. For example, the set processing module 304 may select one or more records 400 having the highest one or more result scores from the consideration set. The set processing module 304 may then transmit one or more record IDs 122 associated with (e.g., included in) the selected records 400 to the result generation module 114.

The result generation module 114 may receive the record IDs 122 and, e.g., the result scores, from the set processing module 304 and identify the (e.g., selected) records 400 of the consideration set in the search data store 112 using the IDs 122. The result generation module 114 may then select record content (e.g., web links, documents, media files, AAMs, WAMs, ADAs, and/or additional information) from the (e.g., selected) records 400 and transmit the selected content to the user device 102 as search results 120, e.g., with the corresponding result scores. The user device 102 may use the result scores associated with the record content (i.e., the search results 120) in a variety of different ways. In some examples, the user device 102 may use the result scores to rank the record content (e.g., one or more user selectable links generated using the content) within a list for display to a user of the device 102. In these examples, a larger result score may indicate that the corresponding portion of the record content (e.g., a given web link, document, media file, app, or state of an app) is more relevant to the search query 116 and, e.g., the indications of the proximate devices 104, their types, and/or their states 118 than another portion of the content having a smaller result score. In examples where the record content is displayed to the user as a list of one or more user selectable links (or “links”), links for portions of the content associated with larger result scores may be displayed higher within the list (e.g., near the top of a screen) than links for portions of the content associated with smaller results scores. In these examples, links for portions of the record content having smaller result scores may be located farther down the list (e.g., off screen) and may be accessed by scrolling down a screen of the user device 102. In this manner, the result scores associated with the record content transmitted by the result generation module 114 to the user device 102 may indicate the relevance of the content (e.g., web links, documents, media files, apps, and/or states of apps) to the search query 116 and, e.g., the proximate devices 104, their types, and/or states, depending on which parameters the set processing module 304 uses to generate the result scores.

FIGS. 4A-4B illustrate example records that may be included in the search data store 112. FIG. 4A illustrates a general example of a record 400A that may be included in the search data store 112. The record 400A of FIG. 4A may include or reference various different data associated with web pages, documents, media files, native or web-based apps, states of native or web-based apps, and/or other information. As shown in FIG. 4A, the record 400A may include a record ID 402A that identifies the record 400A among other records included in the search data store 112. As further shown, the record 400A may include record information 404A, such as a description of the data included in or referenced by the record 400A (e.g., a description of a web page, document, media file, an app, or a state of an app). As described herein, the search system 100 may identify the record 400A in the search data store 112 using (e.g., based on text matches between) a search query 116 and the record information 404A. As also shown, the record 400A may include record content 406A that includes or references the data described by the record information 404A. For example, as shown in FIG. 4A, the record content 406A may include one or more web links (e.g., to web pages), documents (e.g., text), files (e.g., media files, such as image, audio, video, and/or other files), AAMs, WAMs, ADAs, and/or additional data. As also described herein, upon identifying the record 400A using a search query 116, the search system 100 may select the record content 406A from the record 400A and use the content 406A to generate search results 120 that are responsive to the query 116.

FIG. 4B illustrates a specific example of a record 400B that may be included in the search data store 112. The record 400B of FIG. 4B specifies a state of the native app “HP® All-in-One Printer Remote” that enables users to print documents and images using a networked printer (e.g., the HP® Envy 4502 printer). As shown in FIG. 4B, the record 400B includes a record ID “HP ALL-IN-ONE PRINTER REMOTE—PRINT DOCUMENTS/IMAGES” 402B that identifies the record 400B among other records included in the search data store 112. In other examples, the record ID 402B may be represented using one or more characters and/or numbers (e.g., an alphanumeric string, or an index), or machine-readable (e.g., binary) data. As further shown, the record 400B includes record information 404B, including a description of the state specified by the record 400B and user reviews of the state. As also shown, the record 400B includes record content 406B, including one or more AAMs that enable a user device 102 to access the state specified by the record 400B, one or more WAMs that enable the device 102 to access a web equivalent of (e.g., a web page corresponding to) the state, and one or more ADAs that enable the device 102 to download the native app associated with the state (i.e., “HP® All-in-One Printer Remote”). As shown in FIG. 4B, the record content 406B also includes link (e.g., text and/or image) data that enables the user device 102 to generate one or more user selectable links associated with the record content 406B.

FIG. 5A is a flow diagram that illustrates an example method 500A for generating search results 120 based on a search query 116 and one or more of the proximate device(s) 104 using the search system 100. As shown in FIG. 5A, in block 502A, the search system 100 (e.g., the search module 110) may initially receive a search query 116 (e.g., a text string) from one of the user device(s) 102. In block 504A, the search system 100 (e.g., the query analysis module 300) may optionally perform an analysis of the search query 116 (e.g., perform any of tokenization, filtering, stemming, synonymization, and stop word removal with respect to the query 116). In block 506A, the search system 100 (e.g., the search module 110) may also receive an indication of one of the proximate device(s) 104, its type, and/or its state 118 (e.g., a device ID, a type ID, and/or a state ID) from the user device 102. As described with reference to FIG. 6, the user device 102 may have identified the proximate device 104 as being located proximate to the user device 102 using a local wireless network. As further described, the identified proximate device 104 may be configured to communicate via the local wireless network. As also described, to identify the proximate device 104, the user device 102 may have received an indication of the proximate device 104 from the proximate device 104 via the local wireless network. In block 508A, the search system 100 (e.g., the set generation module 302) may identify a consideration set of one or more records 400 included in the search data store 112 based on the search query 116 and the indication 118. In this example, each record may include record content 406 including any of a web link, a document, a media file, an AAM, a WAM, an ADA, and/or other information. For example, the search system 100 may identify the records 400 of the consideration set based on one or more (e.g., text) matches between one or more terms of the search query 116 and one or more terms of the information (e.g., the record information 404) included in the identified records 400. In the example method 500A, the search system 100 may further identify the records 400 based on one or more (e.g., text) matches between the indication 118 (e.g., the device ID, type ID, and/or state ID) and one or more terms of the information (e.g., the record information 404) included in the identified records 400. In block 510A, the search system 100 (e.g., the set processing module 304) may optionally generate one or more result scores for the records 400 included in the consideration set (e.g., generate a result score for each record 400). In block 512A, the search system 100 (e.g., the set processing module 304) may optionally select one or more records 400 from the consideration set based on the one or more result scores associated with the selected records 400 (e.g., select one or more highest-scoring records). In block 514A, the search system 100 (e.g., the result generation module 114) may select the record content 406 (e.g., web links, documents, media files, AAMs, WAMs, ADAs, and/or other information) from the (e.g., selected) records 400 of the consideration set. In block 516A, the search system 100 (e.g., the result generation module 114) may generate one or more search results 120 that include the selected record content 406 (e.g., each result 120 may include the record content 406 selected from each record 400). In block 518A, the search system 100 (e.g., the result generation module 114) may transmit the search results 120 to the user device 102.

FIG. 5B is a flow diagram that illustrates another example method 500B for generating search results 120 based on a search query 116 and one or more of the proximate device(s) 104 using the search system 100. Blocks 502B-504B, 508B, and 512B-518B of the method 500B are analogous to blocks 502A-506A and 512A-518A of the method 500A. In block 506B, the search system 100 (e.g., the set generation module 302) may identify a consideration set of one or more records 400 included in the search data store 112 based on the search query 116, in a similar manner as described with reference to the method 500A. In block 510B, the search system 100 (e.g., the set processing module 304) may generate one or more result scores for the records 400 included in the consideration set based on the indication 118 (e.g., generate a result score for each record 400). For example, the search system 100 may generate the result scores for the records 400 based on how well various aspects of the indication 118 (e.g., the device ID, type ID, and/or state ID) match one or more terms of the information (e.g., the record information 404) included in the identified records 400, e.g., using an MLR model. In block 512B, the search system 100 (e.g., the set processing module 304) may select one or more records 400 from the consideration set based on the one or more result scores associated with the selected records 400, in a similar manner as described with reference to the method 500A. In block 514B, the search system 100 (e.g., the result generation module 114) may select the record content 406 from the selected records 400 of the consideration set, also in a similar manner as described with reference to the method 500A.

FIG. 6 is a flow diagram that illustrates an example method 600 for generating search results 120 based on a search query 116 and one or more of the proximate device(s) 104 using one of the user device(s) 102. As shown in FIG. 6, in block 602, the user device 102 (e.g., the search app 204) may initially receive a search query 116 from a user of the device 102. In block 604, the user device 102 (e.g., the search app 204) may transmit the search query 116 to the search system 100. In block 606, the user device 102 (e.g., the search app 204) may identify one of the proximate device(s) 104 that is located proximate to (e.g., nearby) the device 102 using a local wireless network (e.g., Wi-Fi, Bluetooth, or NFC). In this example, the identified proximate device 104 may be configured to communicate via the local wireless network. Also in this example, to identify the proximate device 104, the user device 102 may receive an indication (e.g., a device ID) of the proximate device 104 from the proximate device 104 via the local wireless network. As described herein, the user device 102 may identify the proximate device 104 using the proximate device identification module 208 included on the device 102 (e.g., as part of the search app 204). Specifically, as one example, the user device 102 may determine a model name, a model number, and/or a device ID of the identified proximate device 104 using the device determination module 210 included in the proximate device identification module 208. As another example, the user device 102 may determine a type (e.g., a type ID) of the identified proximate device 104 using the device type determination module 212 also included in the proximate device identification module 208. As still another example, the user device 102 may determine a state (e.g., a state ID) of the identified proximate device 104 using the device state determination module 214 also included in the proximate device identification module 208.

In block 608, the user device 102 (e.g., the search app 204) may transmit an indication of the identified proximate device 104, its category (e.g., type), and/or its state 118 to the search system 100 (e.g., as a device ID, a type ID, and/or a state ID). As described with reference to FIGS. 5A-5B, the search system 100 may receive the search query 116 and the indication 118 from the user device 102, generate one or more search results 120 based on the query 116 and indication 116, and transmit the results 120 to the device 102. Accordingly, in block 610, the user device 102 (e.g., the search app 204) may receive the search results 120 from the search system 100 in response to transmitting the search query 116 and the indication 118. In block 612, the user device 102 (e.g., the search app 204) may display the search results 120 to the user as one or more user selectable links. As described herein, the search results 120 may include any of web pages, documents, media files, AAMs, WAMs, ADAs, and/or other information. In some examples, as shown in block 614, the user device 102 may detect a user selection of one of the user selectable links, and, as shown in block 616, in response to detecting the user selection, access the content associated with the selected link.

FIGS. 7A-7B illustrate example GUIs that may be generated on one of the user device(s) 102 according to the present disclosure. FIG. 7A depicts an example GUI 115 of a search app 204 executing on the user device 102. As shown in FIG. 7A, a user of the user device 102 has entered a search query “print” 116 into a search field 117 (e.g., a “search box,” or a “search bar”) of the GUI 115. The user has then selected (e.g., touched, or clicked on) a search button 119 of the GUI 115 to cause the search app 204 (e.g., the user device 102) to transmit a query wrapper that includes the search query 116 to the search system 100. In other examples, the user may have caused the search app 204 to transmit the query wrapper to the search system 100 using other techniques (e.g., by touching or clicking another button or GUI element, or via voice command). In the example of FIGS. 7A-7B, the user device 102 (e.g., the search app 204) has also identified one of the proximate device(s) 104, namely a networked printer 104, that is located proximate to (e.g., nearby) the user device 102 using a local wireless network (e.g., Wi-Fi, Bluetooth, or NFC). In this example, the identified proximate device 104 may be configured to communicate via the local wireless network. Also in this example, to identify the proximate device 104, the user device 102 may receive an indication (e.g., a device ID) of the proximate device 104 from the proximate device 104 via the local wireless network. The user device 102 (e.g., the search app 204) has then transmitted an indication of the networked printer 104, its type (e.g., a “networked printer”), and/or its state (e.g., “low ink”) 118 to the search system 100. For example, the user device 102 may have transmitted the indication 118 to the search system 100 with the search query 116 (e.g., as part of the query wrapper), or separately from the query 116 (e.g., prior to or after transmitting the query 116 to the system 100).

The search system 100 has received the search query 116 and the indication of the networked printer 104, its type, and/or its state 118 from the user device 102 and generated one or more search results 120 including, e.g., one or more web pages, documents, media files, AAMs, WAMs, ADAs, and/or other information based on the query 116 and the indication 118. The search system 100 has then transmitted the search results 120 to the user device 102. As described herein, the search system 100 has generated the search results 120 using the search query 116 and the indication 118 such that the results 120 are both responsive to (e.g., match) the query 116 and directly applicable to the networked printer 104. As shown in FIG. 7B, the user device 102 has received the search results 120 from the search system 100 and has displayed the results 120 to the user as one or more user selectable links. As also shown, the user selectable links are configured to, upon being selected by the user, direct the user device 102 to the web pages, documents, media files, AAMs, WAMs, ADAs and/or other information specified by the results 120. Specifically, as shown in FIG. 7B, the user selectable links (e.g., the corresponding search results 120) specify a video user review 600-1 of the networked printer 104 in a web-based or native version of YouTube®, a downloadable (e.g., PDF) user's manual 600-2 associated with the printer 104, a downloadable native app “HP® Smart Print” 600-3 associated with the printer 104, and a state of the app 600-4 that enables the user to print a document or an image using the app and the printer 104 (e.g., by selecting a GUI element 600-5).

In additional examples, the user device 102 may identify the proximate device(s) 104 using any optical communication protocols, interfaces, and technologies, such as wireless infrared communications (e.g., IrDA) and laser-based communications (e.g., using a barcode scanner included in the user device 102 and barcodes present on the proximate device(s) 104). In other examples, the user device 102 may identify the proximate device(s) 104 using a current location of the device 102 (e.g., GPS coordinates associated with the device 102) and a database (e.g., a data store) including an indication of one or more proximate devices 104 and their corresponding geographic locations (e.g., GPS coordinates associated with the devices 104).

The modules and data stores included in the search system 100 represent features or functionality that may be included in the system 100 as it is described in the present disclosure. For example, the search module 110, search data store 112, result generation module 114, and the components thereof may represent features included in the search system 100. The modules and data stores described herein may be embodied by electronic hardware, software, and/or firmware. Depiction of different features or functionality as separate modules or data stores does not necessarily imply whether the modules or data stores are embodied by common or separate electronic hardware, software, and/or firmware. In some implementations, the features or functionality associated with one or more of the modules and data stores depicted herein may be realized by common or separate electronic hardware, software, and/or firmware components.

The modules and data stores may be embodied by electronic hardware, software, and/or firmware components including one or more processing units, memory components, input/output (I/O) components, and interconnect components. The interconnect components may be configured to provide communication between the processing units, memory components, and I/O components. For example, the interconnect components may include one or more buses configured to transfer data between electronic components. The interconnect components may also include one or more control circuits (e.g., a memory controller and/or an I/O controller) configured to control communication between electronic components.

The processing units may include one or more central processing units (CPUs), graphics processing units (GPUs), digital signal processing units (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other processing units. The processing units may be configured to communicate with the memory components and I/O components. For example, the processing units may be configured to communicate with the memory components and I/O components via the interconnect components.

A memory component, or memory, as described herein may include any volatile or non-volatile media. For example, a memory component may include electrical media, magnetic media, and/or optical media, such as random access memory (RAM), non-volatile RAM (NVRAM), read-only memory (ROM), electrically-erasable programmable ROM (EEPROM), Flash memory, solid state drives (SSDs), hard disk drives (HDDs), magnetic tape drives, optical storage technology (e.g., compact disc, digital versatile disc, and/or Blu-ray disc), or any other equivalent or analogous memory components, systems, or devices. The memory components may include (e.g., store) the various types of data described herein. For example, the memory components may store data included in one or more of the records of the search data store 112. The memory components may also include one or more instructions that may be executed by the processing units. For example, the memory components may include one or more computer-readable instructions that, when executed by the processing units, cause the units to perform the various functions attributed to the modules and data stores described herein.

The I/O components may refer to electronic hardware, software, and/or firmware that provide communication with a variety of different devices. For example, the I/O components may provide communication between other devices and the processing units and memory components. In some examples, the I/O components may be configured to communicate with a computer network, such as the network 106. For example, the I/O components may be configured to exchange data over a computer network using any of a variety of different physical connections, wireless connections, and protocols. The I/O components may include one or more network interface components (e.g., a network interface controller), repeaters, network bridges, network switches, routers, and firewalls. In some examples, the I/O components may include hardware, software, and/or firmware configured to communicate with various human interface devices, including display screens, keyboards, pointer devices (e.g., a mouse), touchscreens, speakers, and microphones. In other examples, the I/O components may provide communication with additional devices, such as external memory (e.g., external HDDs).

In some examples, the search system may be a system of one or more computing devices (e.g., a computer search system) configured to implement the techniques described herein. In other words, the features or functionality attributed to the modules and data stores described herein may be implemented by one or more computing devices. Each computing device may include any combination of the electronic hardware, software, and firmware components described herein. Each computing device may also include any combination of the processing units, memory components, I/O components, and interconnect components also described herein. The computing devices of the search system may also include various human interface devices, including display screens, keyboards, pointing devices (e.g., a mouse), touchscreens, speakers, and microphones. The computing devices may also be configured to communicate with additional devices, such as external memory (e.g., external HDDs).

The computing devices of the search system may be configured to communicate with the network 106. The computing devices may also be configured to communicate with one another (e.g., within the search system) via a computer network. In some examples, the computing devices may include one or more server computing devices configured to communicate with user devices, such as the user device(s) 102 (e.g., receive search queries 116 and indications of proximate device(s) 104, their types, and/or their states 118, and transmit search results 120). The server computing devices may also gather data from various data sources, such as the data source(s) 108, index the data, and store the data, as well as gather, index, and/or store other documents or information. The server computing devices may also reside within a single machine or within multiple machines at a single geographic location, or may be distributed across a number of geographic locations.

Additionally, the various implementations of the search system described herein (e.g., using one or more computing devices that include one or more processing units, memory components, I/O components, and interconnect components) are equally applicable to any of the user device(s) 102, as well as to the various components thereof, as described herein. 

What is claimed is:
 1. A method comprising: receiving a search query from a user device; receiving an indication of a proximate device from the user device, wherein the proximate device is located proximate to the user device, wherein the proximate device is configured to communicate via a local wireless network, and wherein the user device receives the indication of the proximate device from the proximate device via the local wireless network; identifying one or more records based on the search query and based on the indication, each record including record content and record information that describes the record content; selecting the record content from the identified one or more records; and transmitting the selected record content to the user device as search results.
 2. The method of claim 1, wherein the indication of the proximate device indicates one or more of a model name, a model number, and a device ID of the proximate device, and wherein identifying the one or more records based on the indication comprises identifying each record based on one or more matches between the one or more of the model name, the model number, and the device ID and one or more terms of the record information included in the record.
 3. The method of claim 1, wherein the indication of the proximate device indicates a category of the proximate device, and wherein identifying the one or more records based on the indication comprises identifying each record based on one or more matches between the category and one or more terms of the record information included in the record.
 4. The method of claim 1, wherein the indication of the proximate device includes one or more terms describing a state of the proximate device, and wherein identifying the one or more records based on the indication comprises identifying each record based on one or more matches between the one or more terms describing the state and one or more terms of the record information included in the record.
 5. The method of claim 1, wherein identifying the one or more records based on the search query comprises identifying each record based on one or more matches between one or more terms of the search query and one or more terms of the record information included in the record.
 6. The method of claim 1, wherein the user device and the proximate device are communicatively coupled via the local wireless network, and wherein the user device receives the indication of the proximate device from the proximate device via the local wireless network as part of the proximate device communicating with the user device.
 7. The method of claim 1, wherein the proximate device is connected to the local wireless network, and wherein the user device receives the indication of the proximate device from the proximate device via the local wireless network in response to the user device performing a scan for computing devices that are connected to the local wireless network.
 8. The method of claim 1, wherein the user device receives the indication of the proximate device from the proximate device via the local wireless network in response to the user device pinging the proximate device via the local wireless network.
 9. The method of claim 1, wherein the proximate device and another computing device are communicatively coupled via the local wireless network, and wherein the user device receives the indication of the proximate device from the proximate device via the local wireless network as part of the proximate device communicating with the other computing device.
 10. The method of claim 1, wherein the local wireless network comprises a Wi-Fi network.
 11. The method of claim 1, wherein the local wireless network comprises a Bluetooth network.
 12. The method of claim 1, wherein the local wireless network comprises a near-field communications (NFC) network.
 13. A method comprising: receiving a search query from a user device; identifying one or more records based on the search query, each record including record content and record information that describes the record content; receiving an indication of a proximate device from the user device, wherein the proximate device is located proximate to the user device, wherein the proximate device is configured to communicate via a local wireless network, and wherein the user device receives the indication of the proximate device from the proximate device via the local wireless network; generating a result score for each of the identified one or more records based on the indication; selecting one or more records from the identified one or more records based on the one or more result scores; selecting the record content from the selected one or more records; and transmitting the selected record content to the user device as search results.
 14. The method of claim 13, wherein the indication of the proximate device indicates one or more of a model name, a model number, and a device ID of the proximate device, and wherein generating the result score for each of the identified one or more records based on the indication comprises generating the result score based on one or more matches between the one or more of the model name, the model number, and the device ID and one or more terms of the record information included in the record.
 15. The method of claim 13, wherein the indication of the proximate device indicates a category of the proximate device, and wherein generating the result score for each of the identified one or more records based on the indication comprises generating the result score based on one or more matches between the category and one or more terms of the record information included in the record.
 16. The method of claim 13, wherein the indication of the proximate device includes one or more terms describing a state of the proximate device, and wherein generating the result score for each of the identified one or more records based on the indication comprises generating the result score based on one or more matches between the one or more terms describing the state and one or more terms of the record information included in the record.
 17. The method of claim 13, wherein generating the result score for each of the identified one or more records based on the indication comprises generating the result score using the indication as a scoring feature input into a machine-learned relevance (MLR) model.
 18. The method of claim 13, wherein identifying the one or more records based on the search query comprises identifying each record based on one or more matches between one or more terms of the search query and one or more terms of the record information included in the record.
 19. A system comprising one or more computing devices configured to: receive a search query from a user device; receive an indication of a proximate device from the user device, wherein the proximate device is located proximate to the user device, wherein the proximate device is configured to communicate via a local wireless network, and wherein the user device receives the indication of the proximate device from the proximate device via the local wireless network; identify one or more records based on the search query and based on the indication, each record including record content and record information that describes the record content; select the record content from the identified one or more records; and transmit the selected record content to the user device as search results.
 20. A system comprising one or more computing devices configured to: receive a search query from a user device; identify one or more records based on the search query, each record including record content and record information that describes the record content; receive an indication of a proximate device from the user device, wherein the proximate device is located proximate to the user device, wherein the proximate device is configured to communicate via a local wireless network, and wherein the user device receives the indication of the proximate device from the proximate device via the local wireless network; generate a result score for each of the identified one or more records based on the indication; select one or more records from the identified one or more records based on the one or more result scores; select the record content from the selected one or more records; and transmit the selected record content to the user device as search results. 